Prediction Intervals of an Alternative Formulation of Partial Least Squares Algorithm

摘要：

The prediction interval is an important property when applies the partial least squares (PLS) to virtual sensor applications. In this work, we propose a new formulation of PLS, such that after projecting out score vectors, the estimated coefficient matrix is obtained as the product of pseudo inverse of the predictor matrix and corresponding weighting matrices. The new formulation, which facilitates the calculation of Jacobian matrix and can be extended to multivariate PLS, is proved to be equivalent to the nonlinear iterative partial least squares (NIPALS). The prediction interval of the algorithm is developed based on the Jacobian of singular vectors. Industrial case studies demonstrate the utility of the algorithm for univariate PLS.

作者: Weilu Lin Elaine Martin

作者单位: Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai School of Chemical Engineering and Advanced Materials,Newcastle University, Newcastle upon Tyne, NE1

会议类型: 国际会议

会议名称: 2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)

会议地点: 杭州

会议语种:英文

页码: 461-465

在线出版日期: 2011-05-01（万方平台首次上网日期，不代表论文的发表时间）